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MAINT: Use more clearly named cumulative risk returns containers.

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Change `_period_returns` to `_cumulative_returns`, so that there
is less mental overhead/confusion when reading through the risk
module.
This commit is contained in:
Eddie Hebert
2014-03-20 16:00:34 -04:00
parent 54ad18e2ff
commit 7ce971fa17
2 changed files with 24 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files
zipline/finance/performance/tracker.py
+1 -1
View File
@@ -289,7 +289,7 @@ class PerformanceTracker(object):
self.all_benchmark_returns[dt])
bench_since_open = \
self.intraday_risk_metrics.benchmark_period_returns[dt]
self.intraday_risk_metrics.benchmark_cumulative_returns[dt]
# if we've reached market close, check on dividends
if dt == self.market_close:
zipline/finance/risk/cumulative.py
+23 -15
View File
@@ -190,8 +190,8 @@ class RiskMetricsCumulative(object):
self.mean_benchmark_returns = None
self.annualized_benchmark_returns = None
self.algorithm_period_returns = pd.Series(index=cont_index)
self.benchmark_period_returns = pd.Series(index=cont_index)
self.algorithm_cumulative_returns = pd.Series(index=cont_index)
self.benchmark_cumulative_returns = pd.Series(index=cont_index)
self.excess_returns = pd.Series(index=cont_index)
self.latest_dt = cont_index[0]
@@ -266,10 +266,10 @@ class RiskMetricsCumulative(object):
self.num_trading_days = len(self.algorithm_returns)
self.algorithm_period_returns[dt] = \
self.calculate_period_returns(self.algorithm_returns)
self.benchmark_period_returns[dt] = \
self.calculate_period_returns(self.benchmark_returns)
self.algorithm_cumulative_returns[dt] = \
self.calculate_cumulative_returns(self.algorithm_returns)
self.benchmark_cumulative_returns[dt] = \
self.calculate_cumulative_returns(self.benchmark_returns)
if not self.algorithm_returns.index.equals(
self.benchmark_returns.index
@@ -307,7 +307,7 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
self.treasury_period_return = \
self.daily_treasury[treasury_end]
self.excess_returns[self.latest_dt] = (
self.algorithm_period_returns[self.latest_dt]
self.algorithm_cumulative_returns[self.latest_dt]
-
self.treasury_period_return)
self.metrics.beta[dt] = self.calculate_beta()
@@ -346,8 +346,14 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
'algo_volatility':
self.metrics.algorithm_volatility[dt],
'treasury_period_return': self.treasury_period_return,
'algorithm_period_return': self.algorithm_period_returns[dt],
'benchmark_period_return': self.benchmark_period_returns[dt],
# Though the two following keys say period return,
# they would be more accurately called the cumulative return.
# However, the keys need to stay the same, for now, for backwards
# compatibility with existing consumers.
'algorithm_period_return':
self.algorithm_cumulative_returns[dt],
'benchmark_period_return':
self.benchmark_cumulative_returns[dt],
'beta': self.metrics.beta[dt],
'alpha': self.metrics.alpha[dt],
'excess_return': self.excess_returns[dt],
@@ -376,17 +382,19 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
return '\n'.join(statements)
def calculate_period_returns(self, returns):
def calculate_cumulative_returns(self, returns):
return (1. + returns).prod() - 1
def update_current_max(self):
if len(self.algorithm_period_returns) == 0:
if len(self.algorithm_cumulative_returns) == 0:
return
if self.current_max < self.algorithm_period_returns[self.latest_dt]:
self.current_max = self.algorithm_period_returns[self.latest_dt]
current_cumulative_return = \
self.algorithm_cumulative_returns[self.latest_dt]
if self.current_max < current_cumulative_return:
self.current_max = current_cumulative_return
def calculate_max_drawdown(self):
if len(self.algorithm_period_returns) == 0:
if len(self.algorithm_cumulative_returns) == 0:
return self.max_drawdown
# The drawdown is defined as: (high - low) / high
@@ -397,7 +405,7 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
# exceed the previous max_drawdown iff the current return is lower than
# the previous low in the current drawdown window.
cur_drawdown = 1.0 - (
(1.0 + self.algorithm_period_returns[self.latest_dt])
(1.0 + self.algorithm_cumulative_returns[self.latest_dt])
/
(1.0 + self.current_max))